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De novo assembly and annotation of the North American bison (Bison bison) reference genome and subsequent variant identification

Authors :
James N. Derr
Eric R. Fritz-Waters
Timothy P. L. Smith
Lauren K. Dobson
James M. Reecy
Steven C. Olsen
J. Blanchong
David P. Alt
Aleksey V. Zimin
Darrell O. Bayles
Source :
Animal geneticsReferences. 52(3)
Publication Year :
2021

Abstract

Genomic tools have improved the ability to manage bison populations and enhanced efforts to conserve this iconic species. These tools have been particularly useful for detecting introgression of cattle genome within bison herds but are limited by the need to use the cattle genome as a surrogate for mapping reads. This complicates efforts to distinguish the species of origin of chromosomal segments in individual bison at the genomic level. An assembly (Bison_UMD1.0) based on 75X genome coverage by Illumina and 454 reads was generated using the MaSuRCA assembler, generating a 2.81 Gigbases de novo reference genome from American bison. Comparison of bison and domestic cattle references identified 28 443 364 single nucleotide variants and 2 627 645 insertions/deletions distinguishing the species. Sequence alignment of an additional 12 modern bison samples and two historic bison samples to domestic cattle and bison references provides a dataset of genomic variants defining the different species and within-species variation. This first annotated draft assembly represents a resource for the management and conservation of bison, as well as a means to study the effects on the genome of interspecies hybridization. The comparisons of historical bison sequences with the new bison reference identified genomic differences between modern and pre-population bottleneck bison. The results support the application of genomics to enhance future research on disease, the establishment of satellite conservation herds and insight into bison and cattle speciation. The first genome assembly for bison and dataset provides a foundation that can be built upon as genetic technologies improve over the years.

Details

ISSN :
13652052
Volume :
52
Issue :
3
Database :
OpenAIRE
Journal :
Animal geneticsReferences
Accession number :
edsair.doi.dedup.....f3f7ce39e5aaea4e52dcb3fddd6f1275